「brainstorm」の検索結果

Use when starting creative work (features, components, functionality, or behavior changes) to clarify user intent, requirements, and design before implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Design abstract strategy games with perfect information, no randomness, and strategic depth. Use when designing a board game, exploring abstract strategy games, brainstorming game mechanics, or evaluating game balance. Keywords: board game, game design, strategy, mechanics, balance.

日本語の概要は準備中です。原文の説明を表示しています。

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

日本語の概要は準備中です。原文の説明を表示しています。

Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.

日本語の概要は準備中です。原文の説明を表示しています。

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Generate project ideas via creative constraints.

日本語の概要は準備中です。原文の説明を表示しています。

Use for non-trivial, design-bearing, or architecture-affecting work before execution planning. Creates or updates a versioned spec under planning/specs/active/ with design intent, alternatives, risks, and acceptance criteria.

日本語の概要は準備中です。原文の説明を表示しています。

Use for non-trivial feature, behavior, workflow, or architecture work before execution planning. Create or update a versioned spec under planning/specs/active with design intent, alternatives, risks, acceptance criteria, and planning readiness.

日本語の概要は準備中です。原文の説明を表示しています。

Refines raw ideas through structured divergent and convergent thinking for ordinary non-command brainstorming, idea shaping, options comparison, and explicit IDEATE deepening routed by `aili-delivery-flow`; do not use as the top-level `/ideate` command owner or for existing-plan stress-test, review, or completion-claim checks.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. Prevents premature implementation, skipped validation, and unreviewed high-risk designs.

日本語の概要は準備中です。原文の説明を表示しています。

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

日本語の概要は準備中です。原文の説明を表示しています。

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

日本語の概要は準備中です。原文の説明を表示しています。

Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/. Classifies incoming tasks and routes to brainstorm, direct edit, or task workflow. Use when beginning a new coding session, resuming work, starting a new task, or re-establishing project context.

日本語の概要は準備中です。原文の説明を表示しています。

Guides collaborative requirements discovery before implementation. Creates task directory, seeds PRD, asks high-value questions one at a time, researches technical choices, and converges on MVP scope. Use when requirements are unclear, there are multiple valid approaches, or the user describes a new feature or complex task.

日本語の概要は準備中です。原文の説明を表示しています。

Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.

日本語の概要は準備中です。原文の説明を表示しています。

Architecture and systems design for agents that retain bounded state across sessions. Covers durable event history, owned state, derived memory, retrieval indexes, framework evaluation, recovery, deletion, and rebuild behavior. Uses constructed implementation examples and workload calibration rather than universal vendor, latency, similarity, retention, or cost claims. Activate on: "always-on agent", "persistent agent architecture", "episodic memory system", "agent memory design", "long-running agent", "stateful agent", "agent that remembers", "MemGPT architecture", "Letta deployment", "/always-on-agent-architecture". NOT for: choosing what data to feed the agent (use always-on-agent-inputs), brainstorming applications (use always-on-agent-applications), safety and privacy concerns (use always-on-agent-safety), general agentic patterns (use agentic-patterns).

日本語の概要は準備中です。原文の説明を表示しています。

Safety-case design for always-on agents with episodic memory. Covers data hygiene, privacy and security risk surfaces, cost controls, scope, user dependency concerns, retention, incident containment, and responsible deployment evidence. It identifies hazards and asks for named controls, tests, owners, and residual uncertainty; it does not provide legal, clinical, youth-safety, or jurisdictional determinations. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).

日本語の概要は準備中です。原文の説明を表示しています。